Effects of riming and melting processes on the rescaled ice particle size distribution

In this study the changes in the rescaled ice particle size distributions due to riming and melting are discussed with use of a cloud microphysical model called Advanced Microphysical Prediction System (AMPS). It is well known that the particle size distributions in aggregation-dominant ice clouds can be rescaled to the universal size distribution, and such useful knowledge has been exploited to better estimate precipitation with remote sensing technology and to parameterize snow size distribution in cloud resolving models. However, challenges in estimating the particle size distributions of ice particles remain in the microphysical processes that typically follow the aggregation, namely riming and melting. This paper attempts to shed lights on the changes of the rescaled size distributions that can occur in typical seeder-feeder stratiform precipitation process.

As a part of AMPS, the authors developed a unique ice microphysical scheme called Spectral Habit Ice Prediction System (SHIPS), which is aimed to retain growth history of ice particles in cloud resolving models. For collection process, this model predicts a circumscribing volume (or maximum dimension) of ice particles by solving a stochastic collection equation with particle property variables. In a 1D model setup, the microphysical simulation will be implemented for five habits: plates, columnar crystals, dendrites, and columnar, planar, and irregular polycrystals, starting from the pristine crystals. A layer of supercooled cloud droplets will be assumed at the lower levels. The mass-dimensional relationships explicitly predicted with SHIPS will be validated against empirical relationships and the rescaled particle size distributions will be discussed along with radar reflectivity and precipitation rate.